• 한국멀티미디어학회논문지
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• 제18권9호
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• pp.1039-1046
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• 2015

We propose a feature generation method for low-resolution face recognition. For this, we first generate new features from the input features (pixels) of a low-resolution face image by adding the higher-order terms. Then, we evaluate the separability of both of the original input features and new features by computing the discriminant distance of each feature. Finally, new data sample used for recognition consists of the features with high separability. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed method gives good recognition performance for low-resolution face images compared with other method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2483-2504
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• 2023

Most existing low-light enhancement algorithms either use a large number of training parameters or lack generalization to real-world scenarios. This paper presents a novel lightweight and robust pixel-wise polynomial approximation-based deep network for low-light image enhancement. For mapping the low-light image to the enhanced image, pixel-wise higher-order polynomials are employed. A deep convolution network is used to estimate the coefficients of these higher-order polynomials. The proposed network uses multiple branches to estimate pixel values based on different receptive fields. With a smaller receptive field, the first branch enhanced local features, the second and third branches focused on medium-level features, and the last branch enhanced global features. The low-light image is downsampled by the factor of 2b-1 (b is the branch number) and fed as input to each branch. After combining the outputs of each branch, the final enhanced image is obtained. A comprehensive evaluation of our proposed network on six publicly available no-reference test datasets shows that it outperforms state-of-the-art methods on both quantitative and qualitative measures.

• 천문학회보
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• 제36권1호
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• pp.57.1-57.1
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• 2011

It has been suggested that merging plays an important role in the formation and the evolution of early-type galaxies (ETGs). Optical-NIR color gradients of ETGs in high density environments are found to be less steep than those of ETGs in low density environments, hinting frequent merger activities in ETGs in high density environments. In order to examine if the flat color gradients are the result of dry mergers, we studied the relations between merging features, color gradient, and environments of 281 low redshift ETGs selected from Sloan Digital Sky Survey (SDSS) Stripe82. The sample contains 222 relaxed ETGs, 38 ETGs with tidal features, 10 galaxies with dust features and 11 galaxies with tidal and dust features, and Near Infrared (NIR) images are taken from UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). We find that r-K color gradients of field sample galaxies are steeper than those of sample ETGs within cluster environments. For the field sample galaxies, a relatively large number of galaxies with peculiar features contribute to the steeper color gradients, while the absence of these peculiar early-type galaxies make color gradients of the cluster sample galaxies intact. In high density environment, ETGs are already evolved and relaxed, resulting flat color gradients. However, in low density environments, a majority of ETGs undergone merging recently which makes the color gradients steep.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.521-524
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• 2013

본 논문에서는 개선된 고차상관 특징계수 통해서 얻어진 특징 정보를 제스처 심볼로 구성하여 인식하는 알고리즘에 대해 기술한다. 제안된 방법은 기존의 기하학적인 특징 기반 방법이나 외관기반 방법의 비해 많은 계산 량이 요구 되지 않고 최소한의 정보를 사용하고도 높은 인식률을 유지 할 수 있기에 실시간 시스템 구축에 매우 적합하다.

• 사상체질의학회지
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• 제29권1호
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• pp.29-39
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• 2017

Objectives Facial features can be utilized as an indicator of Korean medical diagnosis. They are often measured by using the diagnostic device for an objective diagnosis. Accordingly, it is necessary to verify the reliability of the features which are obtained from the device for the accurate diagnosis. In this study, we attempt to evaluate the repeatability of facial feature variables using the Sasang Constitutional Analysis Tool(SCAT) for the Sasang Constitutional face diagnosis. Methods Facial pictures of two subjects were taken 24 times respectively for two days according to a standard guideline. In order to evaluate the repeatability, the coefficient of variation was calculated for the facial features extracted from frontal and profile images. Results The coefficient of variation was less than 10% in most of the facial features except the upper lip, trichion, and chins related features. Conclusions It was confirmed that the coefficient of variation was small in most of the features which enables the objective and reliable analysis of face. However, some features showed the low reliability because the location of facial landmarks related to them is ambiguous. In order to solve the problem, a clear basis for the location discussion is required.

• 대한가정학회지
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• 제46권4호
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• pp.107-117
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• 2008

The aim of this study is to promote an appropriate consumption culture given the features of the segmented female college student group and to utilize these features as basic data at the level of consumer education. The lifestyle of female college students will be identified, along with the current use and customer satisfaction of low price cosmetics that are aimed at this group. The conclusion will be proposed on the basis of the results of this study: Firstly, low price cosmetics producers need to develop products that satisfy the needs of customers and to establish marketing strategies such as sales promotions according to the current trend. Secondly, in order to establish rational purchasing, it is necessary to promote an appropriate consumption culture by offering consumer education to college students. Thirdly, most consumers equate brands with quality. Therefore, companies need to continually produce quality products that may be differentiated from other low price cosmetics, not only in terms of price but also in terms of product quality, in order to enhance the reliability of their brand. Furthermore, it is necessary for consumers to be able to purchase products by considering product quality through searching for diverse information and not merely by depending on any particular brand.

• 한국정보시스템학회지:정보시스템연구
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• 제28권2호
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• pp.181-200
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• 2019

Purpose In order to find out the influential factors to accept the mobile convenient payment service like Apple pay or Samsung Pay based on the Unified Theory of Acceptance and Use of Technology according to the type of High and Low value payments. Design/methodology/approach This research model is designed on the factors of Unified Theory of Acceptance and Use of Technology and simultaneously analysed, or performed the empirical analysis of the PLS-SEM(Partial Least Squares structural equation model) in order to forage for the association among mobile convenient payment service's features. Findings According to the empirical analysis consequence, this research confirmed that the adoption of mobile convenient payment services is influence by features on the basis of Unified Theory of Acceptance and Use of Technology, mobility, and trust. Also, this paper figure out that the behavior of an user acceptance of mobile convenient payment services according to the type of high and low value payments.

• 반도체디스플레이기술학회지
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• 제19권3호
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• pp.1-6
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• 2020

In this paper, a method for improving the defect classification performance in steel plate surface has been studied, based on DWT(discrete wavelet transform) and SVM(support vector machine). Surface images of the steel plate have low contrast, uneven, and featureless, so that the contrast between defect and defect-free regions is not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. In order to improve the characteristics of these images, a synthetic images based on discrete wavelet transform are modeled. Using the synthetic images, edge-based features are extracted and also geometrical features are computed. SVM was configured in order to classify defect images using extracted features. As results of the experiment, the support vector machine based classifier showed good classification performance of 94.3%. The proposed classifier is expected to contribute to the key element of inspection process in smart factory.

• 천문학회보
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• 제37권1호
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• pp.41.2-41.2
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• 2012

It has been suggested that merging plays an important role in the formation and the evolution of early-type galaxies (ETGs). Optical-NIR color gradients of ETGs in high density environments are found to be less steep than those of ETGs in low density environments, hinting frequent merger activities in ETGs in high density environments. In order to examine if the flat color gradients are the result of dry mergers, we studied the relations between merging features, luminosities, environments and color gradients of 196 low redshift ETGs selected from Sloan Digital Sky Survey (SDSS) Stripe82. Near Infrared (NIR) images are taken from UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). Color (r-K) gradients of ETGs with tidal features are a little flatter than relaxed ETGs, but not significant. We found that massive (> 10^11.3 solar masses) ETGs have -40% less scattered color gradients than less massive ETGs. The less scattered color gradients of massive ETGs could be evidence of dry merger processes in the evolution of massive ETGs. We found no relation between color gradients of ETGs and their environments.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권3호
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• pp.209-218
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• 2013

인간의 동작 인식에 대한 이전 연구는 주로 관절체로 표현된 신체 움직임을 추적하고 분류하는데 초점을 맞춰 왔다. 이 방식들은 실제 이미지 사용 환경에서 신체 부위에 대한 정확한 분류가 필요하다는 점이 까다롭기 때문에 최근의 동작 인식 연구 동향은 시공간상의 관심 점과 같이 저수준의, 더 추상적인 외형특징을 이용하는 방식이 일반화되었다. 하지만 몇 년 사이 자세 예측 기술이 발전하면서 자세 기반 방식에 대한 시각을 재정립하는 것이 필요하다. 본 연구는 외형 기반 방식에서 저수준의 외형특징만으로 분류기를 학습시키는 것이 충분한지에 대한 문제를 제기하면서 자세 예측을 이용한 효과적인 자세기반 동작인식 방식을 제안하였다. 이를 위해 다양한 감정을 표현하는 동작 시나리오를 대상으로 외형 기반, 자세 기반 특징 및 두 가지 특징을 조합한 방식을 비교하였다. 실험 결과, 자세 예측을 이용한 자세 기반 방식이 저수준의 외형특징을 이용한 방식보다 감정 동작 분류 및 인식 성능이 더 나았으며 잡음 때문에 심하게 망가진 이미지의 감정 동작 인식에도 자세 예측을 이용한 자세기반의 방식이 효과적이었다.